PPWEB:A Peer-to-Peer Approach forWeb Surfing On the Go Ling-Jyh Chen, Ting-Kai Huang Institute of Information Science, Academia Sinica, Taiwan Guang Yang Nokia Research Center, Palo Alto, US
Motivation • Web surfing is part of our life. • How can we surf the Web when we cannot directly access the web pages? • No connections • Censorship • Mobile devices are hugely popular. • How can we browse the Web when we are on the go? • Cellular • Wi-Fi Hotspots
Previous Solutions • Offline-based approaches • Gnu Wget • Wwwoffle • Well-known web browsers • Cache-based approaches • Push based (Aalto ‘04, Costa-Montenegro ‘02, Spangler ‘97) • Pull based (Jiang ’98a, Jiang ’98b, Padmanabhan ‘96) • Infostation-based approaches • Mobile Hotspots (Ho ‘04) • Thedu (Balasubramanian ‘07)
Previous Solutions (Drawbacks) • Offline-based • manually download web documents • limited number of web pages • Cache-based • Tremendous storage overhead • You still need a data plan to surf. • Infostation-based • Dedicated Infostations needed • Single point of failure
Assumptions We Make • All peers collaborate. • All peers have local connectivity • WiFi, Bluetooth, etc. • All peers are mobile. • Some peers have Internet access.
HTTP What We Propose: Scenario 1 Internet Gateway Peer: A peer who can access the Internet directly
What We Propose: Scenario 2a Gateway Peer (B) Vanilla Peer (A): Peer that cannot access Internet directly
What We Propose: Scenario 2b Vanilla Peer (A) Vanilla Peer (B)
Y N Y N Y N N N Y B gets A’s request B is a GP B and A are connected B has the requested web content Direct forwarding The request has been relayed H times B and A are connected Collaborative forwarding Y Indirect Forwarding Do nothing Request Forwarding
Direct Forwarding vs. Indirect Forwarding • B has complete content =>Direct Forwarding algorithm • B may only have partial content =>Indirect Forwarding algorithm • Further passing the request message using Request Forwardingalgorithm
Cooperative Forwarding Algorithm • Increase the packet delivery ratio and decrease the request response time • HEC-PF • Hybrid Erasure Coding Algorithm (H-EC) • Probabilistic Forwarding Algorithm • Erasure codes increase error tolerance. • Extra caching increases hit ratio in the future (esp. for popular pages).
Evaluations • Evaluate the performance of PPWEB scheme against Mobile Hotspots scheme • Service ratio and traffic overhead • DTNSIM: Java-based simulator • Real wireless traces • UCSD (campus trace) • iMote (Infocom ‘05)
Parameter Settings • Number of VPs: • 20% of the other peers • Number of requests: • first 10% of simulation time with a Poisson rate of 1800 sec/request. • The HTTP requests: • top 500 requested web pages, • campus proxy server of NTU, Apr.-Sept. 2006.
Scenario 1: UCSD γ= 20% γ= 60%
Scenario 2: iMote γ= 20% γ= 60%
Traffic Overhead Replication factor of erasure coding = 2 Aggressive forwarding phase of the HEC-PF: make one more copy The upper bound of the traffic overhead : 2*2=4
Summary • PPWEB is a peer-to-peer solution to enable mobile web surfing. • No constant Internet access is required. • No dedicated servers are required. • It implements a Collaborative Forwardingalgorithm that takes advantage of opportunistic encounters.